2025 November-1 - 222 articles
This paper presents a novel hybrid modulation technique for Asymmetrical Cascaded H-Bridge Multilevel Inverters (ACHBMLIs), specifically designed to enhance both efficiency and harmonic performance. Unlike conventional strategies, the proposed method...
In this study, we investigate the effects of rapid thermal annealing (RTA) in a nitrogen ambient on Al0.8Sc0.2N metal–ferroelectric–metal capacitors. The RTA treatment of up to 13 min on an as-deposited AlScN film markedly improves electr...
Ultra-reliable low-latency communication (URLLC) presents significant challenges in simultaneously guaranteeing stringent latency bounds, ultra-high reliability, and efficient resource utilization under dynamic channel conditions. To address these jo...
This study proposes an integrated control–optimization framework for harmonic mitigation in two-level, grid-connected inverters with battery energy storage operating under unbalanced grid conditions. A proportional–resonant controller in...
The increasing demand for data utilization has renewed attention to the trade-off between privacy protection and data utility, particularly concerning pseudonymized datasets. Traditional methods for evaluating re-identification risk and utility often...
Steganalysis is a critical research direction in the field of information security. Traditional approaches typically employ convolution operations for feature extraction, followed by classification on noise residuals. However, since steganographic si...
This study investigates how increasing prompt complexity affects the performance of Large Language Models (LLMs) across multiple Natural Language Processing (NLP) tasks. We introduce an incremental evaluation framework where six tasks—JSON form...
In today’s rapidly evolving data environment, secure and efficient storage solutions are fundamental to supporting the robust development of the data economy. Trustworthy data space serves as an innovative technological framework for addressing...
Indoor localization based on range measurements in wireless sensor networks involves nonlinear measurement models and is susceptible to non-Gaussian noise, which is associated with complex indoor environments. While particle filters (PFs) are well-su...
The proliferation of artificial intelligence (AI) and online services has significantly escalated the demand for computing and storage resources, which are fundamentally enabled by cloud computing infrastructure. As the backbone of cloud computing se...
To address the limitations of single-sensor perception in inland vessel monitoring and the lack of robustness of traditional tracking methods in occlusion and maneuvering scenarios, this paper proposes a hierarchical multi-target tracking framework t...
Bug localization is a critical task in large-scale software maintenance, as it reduces exploration costs and enhances system reliability. However, existing approaches face limitations due to semantic mismatches between bug reports and source code, in...
The undifferenced and uncombined (UDUC) model preserves raw code and carrier-phase observations for each frequency, avoiding differencing or ionosphere-free combinations. This approach enables the direct estimation of atmospheric parameters. However,...
Zero-shot learning (ZSL) aims to categorize target classes with the aid of semantic knowledge and samples from previously seen classes. In this process, the alignment of visual and attribute modality features is key to successful knowledge transfer....
This paper presents an orthogonal time–frequency space (OTFS)-based integrated sensing and communication (ISAC) framework for vehicular-to-base-station (V2B) scenarios, where a synthetic road environment models vehicular mobility and multipath...
In recent years, remote data management environments have been increasingly deployed across diverse infrastructures, accompanied by a rapid surge in the demand for sharing and collaborative processing of sensitive data. Consequently, ensuring data se...
Steady-state visual evoked potential (SSVEP)-based brain–computer interface (BCI) technology offers a promising solution for wheelchair control by translating neural signals into navigation commands. A major challenge—signal noise caused...
Task scheduling in cloud computing becomes significantly more challenging under Distributed Denial-of-Service (DDoS) attacks, as malicious workload injection disrupts resource availability and degrades Quality of Service (QoS). To address this issue,...
This study introduces a dual-proxy framework for household-adaptive, non-invasive shower detection using standard water-heater logs. The framework leverages proxy at two complementary levels: a feature-level proxy (washing_seconds) that captures wash...
This study addresses the common challenges in medical image segmentation and recognition, including boundary ambiguity, scale variation, and the difficulty of modeling long-range dependencies, by proposing a unified framework based on a hierarchical...
Current denoising algorithms in infrared imaging systems predominantly target either high-frequency stripe noise or Gaussian noise independently, failing to adequately address the prevalent hybrid noise in real-world scenarios. To tackle this challen...
The increasing scale and complexity of graph-structured data necessitate efficient parallel training strategies for graph neural networks (GNNs). The effectiveness of these strategies hinges on the quality of graph feature representation. To this end...
The increasing complexity of the electromagnetic environment poses an increasing risk to unmanned aerial vehicles (UAVs) operating in airspaces subject to adverse electromagnetic effects. This paper investigates the potential electromagnetic interfer...
The proliferation of algorithmically generated malicious URLs necessitates a shift from syntactic detection to semantic analysis. This paper introduces PhishGraph, a disk-aware Approximate Nearest Neighbor (ANN) search system designed to perform bill...
In this paper, we investigate the Adaptive Service Migration (ASM) problem in dynamic satellite edge computing networks, focusing on Low Earth Orbit satellites with time-varying inter-satellite links. We formulate the ASM problem as a constrained opt...
Backscatter technologies promise to enable large-scale, battery-free sensor networks by modulating and reflecting ambient radio frequency (RF) carriers rather than generating new signals. Translating this potential into practical deployments—su...
An early and precise diagnosis is essential for successful intervention in Alzheimer’s disease (AD), a progressive neurological illness. In this study, we present a deep learning-based framework for multiclass classification of AD severity leve...
Ransomware attacks are increasingly resulting in the public leakage of sensitive personal data, affecting both individuals and organizations worldwide. Aimed to inform victims when their personal information is compromised, this paper introduces RDBA...
Wireless contactless human activity sensing is a new type of sensing method that uses the propagation characteristics of wireless signals to accurately perceive and understand human behavior. However, facing the huge amount of newly generated data an...
Safeguarding data confidentiality and enforcing precise access regulation in cloud platforms continue to be major research concerns. Attribute-based encryption (ABE) offers a versatile framework for policy-driven control, whereas public key encryptio...
Ensuring the resilience and efficiency of modern distribution networks is increasingly critical in the presence of distributed energy resources (DERs). This study presents a multi-objective optimization framework based on a Genetic Algorithm (GA) to...
This study investigates the enhancement in spectral efficiency in wireless networks through the application of Non-Orthogonal Multiple Access (NOMA), particularly within the context of imminent 5G networks. Despite its recognized potential, the appli...
Metalenses, a novel class of advanced planar optical devices based on metasurfaces developed in recent years, enable the design of incident light’s amplitude, phase, and polarization with high degrees of freedom to meet application requirements...
The increasing digitalization of energy infrastructures, particularly electric vehicle (EV) charging systems, has expanded their vulnerability to cyber threats. This paper presents a modular AI-driven platform for detecting attacks on EV charging inf...
In the past few years, feature fusion-based violence detection has made remarkable progress. However, existing detection methods primarily focus on temporal feature analysis, which may result in an insufficient representation of the subtle variations...
The increasing adoption of smart home technologies introduces significant cybersecurity and forensic challenges. This necessitates a shift from traditional reactive digital forensics to a more proactive approach to safeguarding these environments. Th...
The widespread use of leetspeak and dialectal Arabic on social media poses a critical challenge to automated hate speech detection systems. Existing Arabic NLP models, largely trained on Modern Standard Arabic (MSA), struggle with obfuscated, noisy,...
This study investigates the vulnerability of Internet of Things (IoT) devices to climate change in Kazakhstan, where extreme seasonal variability and rising climate risks threaten device reliability. Using high-resolution climate projection data from...
Recent advances in foundation models have enabled strong zero-shot performance across vision tasks, yet their effectiveness for fine-grained domains such as food image segmentation remains underexplored. This study investigates the zero-shot capabili...
Due to the diverse needs of users, such as the requirement for rapid charging in time-sensitive situations and the need to minimize battery power consumption to extend battery life when the device is idle, a wireless charging system that combines fas...
Pre-trained visual language models have become excellent basic models for many downstream tasks in transfer learning. However, due to the serious gap between the data scale of downstream tasks and the large-scale data used by pre-trained models, migr...
The boundaries of planar building components characterize the structural outline of buildings and are of great importance in applications such as indoor model reconstruction and localization. However, traditional methods for extracting boundary point...
As drones become increasingly integrated into civilian and industrial domains, the demand for natural and accessible control interfaces continues to grow. Conventional manual controllers require technical expertise and impose cognitive overhead, limi...
This study presents a novel federated learning (FL) methodology implemented directly on STM32-based microcontrollers (MCUs) for energy-efficient smart irrigation. To the best of our knowledge, this is the first work to demonstrate end-to-end FL train...
In this paper, virtual synchronous generator (VSG) technology is innovatively introduced into the distributor-unified power flow controller (D-UPFC) control to simulate the power generation characteristics of the synchronous generator. Concepts such...
Virtual synchronous generator (VSG) simulates the dynamic characteristics of synchronous generator, offering significant advantages in flexibly adjusting virtual inertia and damping parameters. However, their dynamic stability is susceptible to const...
Under the tightening carbon reduction policies, port microgrids face the challenge of optimizing the installed capacity of multiple power generation types to reduce operating costs and increase renewable energy penetration. We develop a bi-level cost...
This paper presents an innovative approach to the modeling and dynamic analysis of DC–DC converters in photovoltaic applications. Departing from traditional studies that focus on the transfer function from duty cycle to output voltage, this wor...
Crowdsourced delivery plays a key role in fresh food retailing, where tight time limits and perishability require fast, reliable fulfillment. However, real-time order–courier assignment is challenging because orders arrive in bursts, couriers&r...
An integrated ESP32-based measurement system called PV-Scope is presented for real-time photovoltaic (PV) module efficiency characterization and small off-grid system testing under field conditions. The system includes pyranometer-calibrated irradian...
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